b = torch.Tensor([[1,2,3],[4,5,6]])
print(b)
index_1 = torch.LongTensor([[0,1],[2,0]])
index_2 = torch.LongTensor([[0,1,1],[0,0,0]])
print (torch.gather(b, dim=1, index=index_1))
print (torch.gather(b, dim=0, index=index_2))

输出：

tensor([[1., 2., 3.],
        [4., 5., 6.]])
tensor([[1., 2.],
        [6., 4.]])
tensor([[1., 5., 6.],
        [1., 2., 3.]])

根据维度dim按照索引列表index从input中选取指定元素
如上述例子，个人理解如下：
又如：

y_hat = torch.tensor([[0.1, 0.3, 0.6], [0.3, 0.2, 0.5]]) 
y = torch.LongTensor([0, 2])
y_hat.gather(1, y.view(-1, 1))

输出：

tensor([[0.1000],
        [0.5000]])

官方文档的解释

torch.gather(input, dim, index, out=None) → Tensor

    Gathers values along an axis specified by dim.

    For a 3-D tensor the output is specified by:

    out[i][j][k] = input[index[i][j][k]][j][k]  # dim=0
    out[i][j][k] = input[i][index[i][j][k]][k]  # dim=1
    out[i][j][k] = input[i][j][index[i][j][k]]  # dim=2

    Parameters: 

        input (Tensor) – The source tensor
        dim (int) – The axis along which to index
        index (LongTensor) – The indices of elements to gather
        out (Tensor, optional) – Destination tensor

    Example:

    >>> t = torch.Tensor([[1,2],[3,4]])
    >>> torch.gather(t, 1, torch.LongTensor([[0,0],[1,0]]))
     1  1
     4  3
    [torch.FloatTensor of size 2x2]